The present invention relates to an information processing system, an information output apparatus and method, an information processing apparatus and method, a recording medium, and a program, and particularly to an information processing system in which an unevaluated new item can be recommended to a user, an information output apparatus and method, an information processing apparatus and method, a recording medium, and a program.
Conventionally, in an apparatus (hereinafter referred to as a recommendation apparatus) which selects (filters) information, a commodity, a service, a television program, a radio program or the like in accordance with an interest, taste or the like of each user, and recommends or provides it to each user, content based filtering or cooperation filtering has been used as the selection method.
For example, in the case where a book is selected from among plural books by content based filtering, and is recommended to a user, a keyword as a selection basis is previously set in the apparatus. When the filtering is performed, it is determined whether the previously set keyword exists in documents regarding books, and only a book containing the keyword in the document is selected and recommended to the user. Most conventional filtering adopts content based filtering.
Next, in the case where cooperation filtering is performed for plural books, first, a user group similar to a certain user in preference (books to be purchased are similar to each other) is previously specified. Then, a book selected by many users in the specified user group is recommended to the user.
However, in the recommendation apparatus adopting content based filtering, there has been a problem that selected items as objects of the filtering are limited to those which can be understood by a computer.
Besides, in the recommendation apparatus adopting content based filtering, there has been a problem that a judgment can be made based only on given information, such as a keyword, and a rule.
Further, in the recommendation apparatus adopting content based filtering, since an item recommended to a user is selected from among plural given selection items on the basis of a predetermined rule, there has been a problem that the item recommended to the user can be selected only from among the given items.
On the other hand, in the recommendation apparatus adopting cooperation filtering, a user group with a similar preference tendency is specified on the basis of the preference tendency of the user, and an item indicated by many users of the specified user group is recommended to the user, so that an object recommended to the user can be selected from among unspecific items.
However, in conventional recommendation apparatus adopting cooperation filtering, it is necessary that many users using the system evaluate plural items in advance, and there has been a problem that a load is imposed on the users. That is, for example, in the case of an apparatus for recommending a television program to a user, the user must evaluate a program each time he or she views the program, and this is very troublesome.
Besides, in conventional recommendation apparatus adopting cooperation filtering, there has been a problem that recommended items are limited to items already evaluated by other users. That is, for example, in the case where a television program is recommended to a user, although a program broadcast periodically, for example, every day or every week, or a program broadcast in series can be recommended, an unbroadcasted program has not been evaluated by users, and therefore cannot be recommended.